Finding Hidden Faces In Google Earth's Landscapes

A design studio in Berlin applied face-tracking technology to Earth’s surface, and found faces staring back.

In a neat video on data visualization that we posted the other day, the narrator identifies Google Maps as one of the most commonly seen visualizations in the world. The influence of such widely available information provides so much fodder for new modes of expression, like these contrasted glitches in Earth’s surface, or Google Earth photography pieces that appeared this year at the Met, that artistic interpretations of Google Maps or Earth practically deserves its own subgenre.

The Berlin-based generative design duo Onformative have made an entry into the category, with Google Faces. Everyone knows the game: Lie down somewhere upside, gaze upwards, and find faces among the Rorschach tufts of clouds in the sky. Onformative played the game to create the Google Faces gallery, but instead of using the human eye, they put face-tracking technology to use.

Cedric Kiefer, cofounder of Onformative, says they stumbled across the project while working on another assignment that used the same technology. "At the beginning we had a high rate of false positives, and we asked ourselves what causes the computer to see a face in something else," he tells Co.Design. "[It’s] a phenomenon that is called pareidolia, the tendency to see faces in clouds or nature. We were curious to find out how the psychological phenomenon of pareidolia could be generated by a machine."

The scanning technology in question runs on an algorithm that detects the right combinations of light and dark spaces. Kiefer based the tracking on work done by a developer named Jason Saragih, and synced it to Google Maps. The face recognition robot browsed Earth’s surface at it’s own leisure, for hours on end but, surprisingly, didn’t make it very far: "Although the bot was running nonstop for several weeks, we just traveled a small part of the world in different zoom levels."

The robot still submits plenty of false positives. Some results are compelling, but so "subjective" that Kiefer decided to focus the project on faces that register as accurate for the human eye, even though the machine’s eye is more conceptually artistic. "It was proof that machines can actually find pareidolia that also works for humans."